Call For Papers

==== Final Call for Participation ====

SemEval-2017 Task 7:
Detection and Interpretation of English Puns

http://alt.qcri.org/semeval2017/task7/

Researchers and industry professionals are invited to participate in a
shared task on the computational detection and interpretation of English
puns. The task will occur as part of the SemEval-2017 workshop, to be
collocated with the 55th Annual Meeting of the Association for
Computational Linguistics in Vancouver, Canada on August 3-4, 2017.
SemEval is an ongoing series of evaluations of computational
semantic analysis systems, organized under the aegis of SIGLEX, the
Special Interest Group on the Lexicon of the Association for
Computational Linguistics.

---- Task description ----

A pun is a form of wordplay in which one signifier (e.g., a word or
phrase) suggests two or more meanings by exploiting polysemy, or
phonological similarity to another signifier, for an intended humorous
or rhetorical effect. Puns where the two meanings share the same
spelling are known as homographic, whereas those where the two meanings
are spelled (and also usually pronounced) differently are known as
heterographic.

Conscious or tacit linguistic knowledge -- particularly of lexical
semantics and phonology -- is an essential prerequisite for the
production and interpretation of puns. This has long made them an
attractive subject of study in theoretical linguistics, and has led to a
small but growing body of research into puns in computational
linguistics. This SemEval shared task will be the first organized
evaluation of automatic pun processing systems.

Participants will be provided with two data sets. The first data set
will contain several hundred short contexts (jokes, slogans, aphorisms,
etc.). In some of these contexts, a single word will be used as a
homographic pun; in the rest, there will be no pun. The second data set
will be similar to the first, except that the puns will be heterographic
rather than homographic. For one or both data sets, participating
systems will compete in any or all of three subtasks:

Subtask 1: Pun detection. For this subtask, participants are given an
entire raw data set. For each context, the system must decide whether or
not it contains a pun.

Subtask 2: Pun location. For this subtask, the contexts not containing
puns are removed from the data set. For each context, the system must
identify which word is the pun.

Subtask 3: Pun interpretation. For this subtask, the pun word in each
context is marked, and contexts where the pun's two meanings are not
found in WordNet are removed from the data set. For each context, the
system must annotate the two meanings of the given pun by reference to
WordNet sense keys.

System performance will be measured with the usual metrics from
information retrieval and WSD. Please see the task website for further
details.